EP3695333A1 - Acoustic effects of a mesh on a fluid flow - Google Patents
Acoustic effects of a mesh on a fluid flowInfo
- Publication number
- EP3695333A1 EP3695333A1 EP18866750.5A EP18866750A EP3695333A1 EP 3695333 A1 EP3695333 A1 EP 3695333A1 EP 18866750 A EP18866750 A EP 18866750A EP 3695333 A1 EP3695333 A1 EP 3695333A1
- Authority
- EP
- European Patent Office
- Prior art keywords
- interface
- fluid flow
- simulation
- sound waves
- porous material
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
- 239000012530 fluid Substances 0.000 title claims abstract description 86
- 230000000694 effects Effects 0.000 title claims abstract description 18
- 238000004088 simulation Methods 0.000 claims abstract description 64
- 239000011148 porous material Substances 0.000 claims abstract description 29
- 238000000034 method Methods 0.000 claims description 51
- 238000004590 computer program Methods 0.000 claims description 10
- 230000008859 change Effects 0.000 claims description 9
- 238000013016 damping Methods 0.000 claims description 9
- 230000000670 limiting effect Effects 0.000 claims description 4
- 238000012545 processing Methods 0.000 abstract description 16
- 239000002245 particle Substances 0.000 description 125
- 230000004907 flux Effects 0.000 description 31
- 239000013598 vector Substances 0.000 description 21
- 238000009826 distribution Methods 0.000 description 19
- 238000013459 approach Methods 0.000 description 17
- 238000005315 distribution function Methods 0.000 description 15
- 230000003993 interaction Effects 0.000 description 14
- 239000000463 material Substances 0.000 description 11
- 230000008569 process Effects 0.000 description 11
- 238000010521 absorption reaction Methods 0.000 description 10
- 230000009471 action Effects 0.000 description 7
- 230000006399 behavior Effects 0.000 description 5
- 238000004891 communication Methods 0.000 description 5
- 238000012546 transfer Methods 0.000 description 5
- 238000004880 explosion Methods 0.000 description 4
- 230000002829 reductive effect Effects 0.000 description 4
- 230000008901 benefit Effects 0.000 description 3
- 230000001419 dependent effect Effects 0.000 description 3
- 230000006870 function Effects 0.000 description 3
- 230000003287 optical effect Effects 0.000 description 3
- 239000011358 absorbing material Substances 0.000 description 2
- 238000005094 computer simulation Methods 0.000 description 2
- 238000011960 computer-aided design Methods 0.000 description 2
- 238000012937 correction Methods 0.000 description 2
- 230000007423 decrease Effects 0.000 description 2
- 239000004744 fabric Substances 0.000 description 2
- 238000009434 installation Methods 0.000 description 2
- 239000000203 mixture Substances 0.000 description 2
- 230000036961 partial effect Effects 0.000 description 2
- 230000009467 reduction Effects 0.000 description 2
- 238000013515 script Methods 0.000 description 2
- 238000000926 separation method Methods 0.000 description 2
- 239000007787 solid Substances 0.000 description 2
- 230000002547 anomalous effect Effects 0.000 description 1
- 230000004888 barrier function Effects 0.000 description 1
- 239000011111 cardboard Substances 0.000 description 1
- 230000001364 causal effect Effects 0.000 description 1
- 230000001413 cellular effect Effects 0.000 description 1
- 230000003247 decreasing effect Effects 0.000 description 1
- 238000011038 discontinuous diafiltration by volume reduction Methods 0.000 description 1
- 238000002474 experimental method Methods 0.000 description 1
- 239000006260 foam Substances 0.000 description 1
- 238000009472 formulation Methods 0.000 description 1
- 239000004973 liquid crystal related substance Substances 0.000 description 1
- 230000007246 mechanism Effects 0.000 description 1
- 239000012528 membrane Substances 0.000 description 1
- 239000002184 metal Substances 0.000 description 1
- 230000008447 perception Effects 0.000 description 1
- 239000004033 plastic Substances 0.000 description 1
- 229920003023 plastic Polymers 0.000 description 1
- 230000004044 response Effects 0.000 description 1
- 230000002441 reversible effect Effects 0.000 description 1
- 239000004065 semiconductor Substances 0.000 description 1
- 230000001953 sensory effect Effects 0.000 description 1
- 238000010561 standard procedure Methods 0.000 description 1
- 230000003746 surface roughness Effects 0.000 description 1
- 239000004753 textile Substances 0.000 description 1
- 238000011282 treatment Methods 0.000 description 1
- 230000000007 visual effect Effects 0.000 description 1
- 239000002023 wood Substances 0.000 description 1
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/20—Design optimisation, verification or simulation
- G06F30/25—Design optimisation, verification or simulation using particle-based methods
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/20—Design optimisation, verification or simulation
- G06F30/23—Design optimisation, verification or simulation using finite element methods [FEM] or finite difference methods [FDM]
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/10—Geometric CAD
- G06F30/15—Vehicle, aircraft or watercraft design
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/20—Design optimisation, verification or simulation
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2113/00—Details relating to the application field
- G06F2113/08—Fluids
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2119/00—Details relating to the type or aim of the analysis or the optimisation
- G06F2119/10—Noise analysis or noise optimisation
Definitions
- This description relates to computer simulation of physical processes, such as fluid flow and acoustics.
- High Reynolds number flow has been simulated by generating discretized solutions of the Navier-Stokes differential equations by performing high-precision floating point arithmetic operations at each of many discrete spatial locations on variables representing the macroscopic physical quantities (e.g., density, temperature, flow velocity).
- Another approach replaces the differential equations with what is generally known as lattice gas (or cellular) automata, in which the macroscopic-level simulation provided by solving the Navier-Stokes equations is replaced by a microscopic-level model that performs operations on particles moving between sites on a lattice.
- the description describes one or more processing devices and one or more hardware storage devices storing instructions that are operable, when executed by the one or more processing devices, to cause the one or more processing devices to perform operations including modeling the porous material as a two- dimensional interface, in a simulation space, in which fluid flows and sound waves travel through the porous material and experience pressure and acoustic losses.
- the operations also include simulating, in the simulation space, fluid flow and propagation of sound waves, the activity of the fluid being simulated so as to simulate movement of elements within the simulation space and across the interface, where the simulation of the movement of the elements across the interface is governed by the model.
- a system of one or more computers can be configured to perform particular operations or actions by virtue of having software, firmware, hardware, or a combination of them installed on the system that in operation causes or cause the system to perform the actions.
- One or more computer programs can be configured to perform particular operations or actions by virtue of including instructions that, when executed by data processing apparatus, cause the apparatus to perform the actions.
- Implementations of the disclosure may include one or more of the following operations, alone or in combination.
- the operations may further identifying changes to the fluid flow and propagation of sound waves within the simulation space attributable to the interface.
- Generating the measure of the fluid flow across the interface may be determined based on geometrical and simulation characteristics of the porous material.
- Simulating the propagation of sound waves may include calculating a change in pressure from a first side of the interface to a second side of the interface.
- the operations may include determining the acoustic damping characteristics of the porous material based on the simulation.
- Simulating the fluid flow and propagation of sound waves ma include simulating the first side of the interface independently of the second side of the interface.
- Simulating the propagation of sound waves may include allowing unlimited fluid flow through one direction of the interface while limiting the fluid flow in the other direction based on the measure of the fluid flow across the interface.
- the porous material may be a mesh.
- Some advantages of the systems described herein include simplified handling of the complex interface, exact satisfaction of conservation laws, and easy realization of specified fluid boundary conditions on interface.
- FIGS. 1 and 2 illustrate velocity components of two LBM models.
- FIG. 3 is a flow chart of a procedure followed by a physical process simulation system.
- FIG. 4 is a perspective view of a microblock.
- FIGS. 5A and 5B are illustrations of lattice structures used by the system of FIG.
- FIGS. 6 and 7 illustrate variable resolution techniques.
- FIG. 8 illustrates regions affected by a facet of a surface.
- FIG. 9 illustrates movement of particles from a voxel to a surface.
- FIG. 10 illustrates movement of particles from a surface to a surface.
- FIG. 11 is a flow chart of a procedure for performing surface dynamics.
- FIG. 12 illustrates an interface between voxels of different sizes.
- FIG. 13 is a flow chart of a procedure for simulating interactions with facets under variable resolution conditions.
- FIG.14 is an illustration of a mesh.
- FIG. 15 is a schematic view of interface describing the mesh.
- Airflow can be a cause of noise generation in an environment.
- One extreme case of noise caused by airflow is airframe noise.
- Airframe noise can be generated by the flow of air interacting with solid bodies causing a turbulent flow, for example, flows of air interacting with landing gears and lifting surfaces (such as slotted slaps, flaps side-edges, slat side-edges and cavities, flats and slat tracks, slat track cutouts, spoilers, and gear- wake / flap interactions).
- Airframe noise has been described as a lower bound in the amount of noise generated by an aircraft. That is, the airframe noise may define the minimum amount of noise that will be generated by an aircraft.
- Fairings can be designed to redirect all airflow around an area or may be partially flow transparent (for example, made out of meshes or elastic cloth).
- Noise caused by the flow of air can be reduced or eliminated using perforated or slotted sheets or panels of various materials including metal, wood, plastics or cardboard. These sheets or panels can be used as acoustic treatments to absorb sound and reduce noise generation. They can be of various thicknesses and shapes. They can be profiled or un-profiled and can be made curved to fit mounting on curved surfaces.
- a given volumetric model for sound propagation in an absorbing material can be put in the form of a locally-reacting, frequency-dependent, complex impedance at the interface between two different media.
- impedance models may be used in approaches such as the Boundary Element Methods (BEM), the Finite Elements Methods (FEM), and the Statistical Energy Analysis (SEA) methods, and may be implemented as boundary conditions in the frequency domain.
- BEM Boundary Element Methods
- FEM Finite Elements Methods
- SEA Statistical Energy Analysis
- CFD Computational Fluid Dynamics
- CAA Computational Aero Acoustics
- Another approach includes modeling of absorbing materials as volumetric fluid regions, such that sound waves travel through the material and dissipate via a momentum sink.
- This is analogous to the method for macroscopic modeling of flow through porous media achieved by relating the momentum sink to the flow resistance of the material following Darcy's law.
- For acoustic absorption modeling there is the question of how to determine the momentum sink to achieve a desired absorption behavior. If the acoustic absorption is governed (or at least dominated) by the same physical mechanisms as the flow resistivity, then the same momentum sink behavior used to achieve the correct flow resistivity for a particular porous material should also achieve the correct acoustic absorption for that material.
- This approach may be applicable for any passive and homogeneous porous material.
- the approach eliminates numerical stability problems since the impedance is realized in a way that satisfies passive, causal, and real conditions.
- LBM Lattice Boltzmann Method
- a time- explicit CFD/CAA solution method based on the Lattice Boltzmann Method (LBM), such as the PowerFLOW system available from Exa Corporation of Burlington, Massachusetts.
- LBM starts from a "mesoscopic" Boltzmann kinetic equation to predict macroscopic fluid dynamics.
- the resulting compressible and unsteady solution method may be used for predicting a variety of complex flow physics, such as aeroacoustics and pure acoustics problems.
- a porous media model is used to represent the flow resistivity of various components, such as air filters, radiators, heat exchangers, evaporators, and other components, which are encountered in simulating flow, such as through HVAC systems, vehicle engine compartments, and other applications.
- a general discussion of a LBM-based simulation system is provided below and followed by a discussion of a volumetric modeling approach for acoustic absorption and other phenomena and a porous media interface model that may be used to support such a volumetric modeling approach.
- fluid flow may be represented by the distribution function values f i , evaluated at a set of discrete velocities c t .
- This equation is the well-known lattice Boltzmann equation that describe the time- evolution of the distribution function, f t .
- the left-hand side represents the change of the distribution due to the so-called “streaming process.”
- the streaming process is when a pocket of fluid starts out at a grid location, and then moves along one of the velocity vectors to the next grid location.
- the "collision factor” i.e., the effect of nearby pockets of fluid on the starting pocket of fluid, is calculated.
- the fluid can only move to another grid location, so the proper choice of the velocity vectors is necessary so that all the components of all velocities are multiples of a common speed.
- the right-hand side of the first equation is the aforementioned "collision operator" which represents the change of the distribution function due to the collisions among the pockets of fluids.
- the particular form of the collision operator used here is due to Bhatnagar, Gross and Krook (BGK). It forces the distribution function to go to the prescribed values given by the second equation, which is the "equilibrium" form.
- Equation (3) the collective values of c i and w t define a LBM model.
- the LBM model can be implemented efficiently on scalable computer platforms and run with great robustness for time unsteady flows and complex boundary conditions.
- a standard technique of obtaining the macroscopic equation of motion for a fluid system from the Boltzmann equation is the Chapman-Enskog method in which successive approximations of the full Boltzmann equation are taken.
- a small disturbance of the density travels at the speed of sound.
- the speed of the sound is generally determined by the temperature.
- the importance of the effect of compressibility in a flow is measured by the ratio of the characteristic velocity and the sound speed, which is known as the Mach number.
- a first model (2D-1) 100 is a two-dimensional model that includes 21 velocities. Of these 21 velocities, one (105) represents particles that are not moving; three sets of four velocities represent particles that are moving at either a normalized speed (r) (110-113), twice the normalized speed (2r) (120-123), or three times the normalized speed (3r) (130-133) in either the positive or negative direction along either the x ory axis of the lattice; and two sets of four velocities represent particles that are moving at the normalized speed (r) (140-143) or twice the normalized speed (2r) (150-153) relative to both of the x and lattice axes.
- a second model (3D-1) 200 is a three-dimensional model that includes 39 velocities, where each velocity is represented by one of the arrowheads of FIG. 2. Of these 39 velocities, one represents particles that are not moving; three sets of six velocities represent particles that are moving at either a normalized speed (r), twice the normalized speed (2r), or three times the normalized speed (3r) in either the positive or negative direction along the x, y or z axis of the lattice; eight represent particles that are moving at the normalized speed (r) relative to all three of the x, y, z lattice axes; and twelve represent particles that are moving at twice the normalized speed (2r) relative to two of the x, y, z lattice axes.
- More complex models such as a 3D-2 model includes 101 velocities and a 2D-2 model includes 37 velocities also may be used.
- the velocities are more clearly described by their component along each axis as documented in Tables 1 and 2 respectively.
- one represents particles that are not moving (Group 1); three sets of six velocities represent particles that are moving at either a normalized speed (r), twice the normalized speed (2r), or three times the normalized speed (3r) in either the positive or negative direction along the x, y or z axis of the lattice (Groups 2, 4, and 7); three sets of eight represent particles that are moving at the normalized speed (r), twice the normalized speed (2r), or three times the normalized speed (3r) relative to all three of the x, y, z lattice axes (Groups 3, 8, and 10); twelve represent particles that are moving at twice the normalized speed (2r) relative to two of the x, y, z lattice axes (Group 6); twenty four represent particles that are moving at the normalized speed (r) and twice the normalized speed (2r) relative to two of the x, y, z lattice axes, and not moving
- one represents particles that are not moving (Group 1); three sets of four velocities represent particles that are moving at either a normalized speed (r), twice the normalized speed (2r), or three times the normalized speed (3r) in either the positive or negative direction along either the x or y axis of the lattice (Groups 2, 4, and 7); two sets of four velocities represent particles that are moving at the normalized speed (r) or twice the normalized speed (2r) relative to both of the x and y lattice axes; eight velocities represent particles that are moving at the normalized speed (r) relative to one of the x and lattice axes and twice the normalized speed (2r) relative to the other axis; and eight velocities represent particles that are moving at the normalized speed (r) relative to one of the x dy lattice axes and three times the normalized speed (3r) relative to the other axis.
- the LBM models described above provide a specific class of efficient and robust discrete velocity kinetic models for numerical simulations of flows in both two-and three- dimensions.
- a model of this kind includes a particular set of discrete velocities and weights associated with those velocities.
- the velocities coincide with grid points of Cartesian coordinates in velocity space which facilitates accurate and efficient implementation of discrete velocity models, particularly the kind known as the lattice Boltzmann models. Using such models, flows can be simulated with high fidelity.
- a physical process simulation system operates according to a procedure 300 to simulate a physical process such as fluid flow.
- a simulation space is modeled as a collection of voxels (step 302).
- the simulation space is generated using a computer-aided-design (CAD) program.
- CAD computer-aided-design
- a CAD program could be used to draw a micro-device positioned in a wind tunnel.
- data produced by the CAD program is processed to add a lattice structure having appropriate resolution and to account for objects and surfaces within the simulation space.
- the resolution of the lattice may be selected based on the Reynolds number of the system being simulated.
- the Reynolds number is related to the viscosity (v) of the flow, the characteristic length (L) of an object in the flow, and the characteristic velocity ( «) of the flow:
- the characteristic length of an object represents large scale features of the object. For example, if flow around a micro-device were being simulated, the height of the micro-device might be considered to be the characteristic length.
- the resolution of the simulation may be increased, or areas of increased resolution may be employed around the regions of interest.
- the dimensions of the voxels decrease as the resolution of the lattice increases.
- the state space is represented as fi (x, t), where fi represents the number of elements, or particles, per unit volume in state i (i.e., the density of particles in state i) at a lattice site denoted by the three-dimensional vector x at a time t. For a known time increment, the number of particles is referred to simply as fi (x).
- fi (x) the number of particles is referred to simply as fi (x).
- f(x) The combination of all states of a lattice site.
- the number of states is determined by the number of possible velocity vectors within each energy level.
- the velocity vectors consist of integer linear speeds in a space having three dimensions: x, y, and z.
- the number of states is increased for multiple- species simulations.
- Each state i represents a different velocity vector at a specific energy level (i.e., energy level zero, one or two).
- the velocity Ci of each state is indicated with its "speed" in each of the three dimensions as follows:
- Ci (ci,x, Ci, y , Ci,z).
- Energy level one states represent particles having a ⁇ l speed in one of the three dimensions and a zero speed in the other two dimensions.
- Energy level two states represent particles having either a ⁇ 1 speed in all three dimensions, or a ⁇ 2 speed in one of the three dimensions and a zero speed in the other two dimensions.
- Generating all of the possible permutations of the three energy levels gives a total of 39 possible states (one energy zero state, 6 energy one states, 8 energy three states, 6 energy four states, 12 energy eight states and 6 energy nine states.).
- Each voxel (i.e., each lattice site) is represented by a state vector ⁇ ( ⁇ ).
- the state vector completely defines the status of the voxel and includes 39 entries.
- the 39 entries correspond to the one energy zero state, 6 energy one states, 8 energy three states, 6 energy four states, 12 energy eight states and 6 energy nine states.
- the voxels are grouped in 2x2x2 volumes called microblocks.
- the microblocks are organized to permit parallel processing of the voxels and to minimize the overhead associated with the data structure.
- a short-hand notation for the voxels in the microblock is defined as N ( «), where n represents the relative position of the lattice site within the microblock and n ⁇ 0, 1,2, . . . , 7 ⁇ .
- a microblock is illustrated in FIG. 4.
- a surface S (FIG. 3A) is represented in the simulation space (FIG. 5B) as a collection of facets F a :
- each facet F a has a unit normal ( « «), a surface area (A a ), a center location (x «), and a facet distribution function (fi(a)) that describes the surface dynamic properties of the facet.
- different levels of resolution may be used in different regions of the simulation space to improve processing efficiency.
- the region 650 around an object 655 is of the most interest and is therefore simulated with the highest resolution.
- decreasing levels of resolution i.e., expanded voxel volumes
- regions 660, 665 that are spaced at increasing distances from the object 655.
- a lower level of resolution may be used to simulate a region 770 around less significant features of an object 775 while the highest level of resolution is used to simulate regions 780 around the most significant features (e.g., the leading and trailing surfaces) of the object 775.
- Outlying regions 785 are simulated using the lowest level of resolution and the largest voxels.
- Voxels affected by one or more facets are identified (step 304).
- Voxels may be affected by facets in a number of ways.
- a voxel that is intersected by one or more facets is affected in that the voxel has a reduced volume relative to non-intersected voxels. This occurs because a facet, and material underlying the surface represented by the facet, occupies a portion of the voxel.
- a fractional factor ⁇ Pf(x) indicates the portion of the voxel that is unaffected by the facet (i.e., the portion that can be occupied by a fluid or other materials for which flow is being simulated).
- Pf (x) equals one.
- Voxels that interact with one or more facets by transferring particles to the facet or receiving particles from the facet are also identified as voxels affected by the facets. All voxels that are intersected by a facet will include at least one state that receives particles from the facet and at least one state that transfers particles to the facet. In most cases, additional voxels also will include such states.
- a facet F a receives particles from, or transfers particles to, a region defined by a parallelepiped G w . having a height defined by the magnitude of the vector dot product of the velocity vector a and the unit normal n a of the facet (
- the facet F a receives particles from the volume V m . when the velocity vector of the state is directed toward the facet (
- this expression must be modified when another facet occupies a portion of the parallelepiped G m , a condition that could occur in the vicinity of non-convex features such as interior corners.
- the parallelepiped G w . of a facet F a . may overlap portions or all of multiple voxels.
- the number of voxels or portions thereof is dependent on the size of the facet relative to the size of the voxels, the energy of the state, and the orientation of the facet relative to the lattice structure.
- the number of affected voxels increases with the size of the facet. Accordingly, the size of the facet, as noted above, is typically selected to be on the order of or smaller than the size of the voxels located near the facet.
- the portion of a voxel N(x) overlapped by a parallelepiped G m . is defined as V w .(x).
- the flux Y w .(x) of state i particles that move between a voxel N(x) and a facet Fa. equals the density of state i particles in the voxel (Ni(x)) multiplied by the volume of the region of overlap with the voxel (Vw.(x))
- N,a ⁇ Va(x) + ⁇ ⁇ ⁇ .( ⁇ ) Eq.(10) where the first summation accounts for all voxels overlapped by G m . and the second term accounts for all facets that intersect G m .
- this expression reduces to:
- a timer is initialized to begin the simulation (step 306).
- movement of particles from voxel to voxel is simulated by an advection stage (steps 308-316) that accounts for interactions of the particles with surface facets.
- a collision stage (step 318) simulates the interaction of particles within each voxel.
- the timer is incremented (step 320). If the incremented timer does not indicate that the simulation is complete (step 322), the advection and collision stages (steps 308-320) are repeated. If the incremented timer indicates that the simulation is complete (step 322), results of the simulation are stored and/or displayed (step 324).
- each facet must meet four boundary conditions.
- the combined mass of particles received by a facet must equal the combined mass of particles transferred by the facet (i.e., the net mass flux to the facet must equal zero).
- the combined energy of particles received by a facet must equal the combined energy of particles transferred by the facet (i.e., the net energy flux to the facet must equal zero).
- the other two boundary conditions are related to the net momentum of particles interacting with a facet.
- the net tangential momentum flux must equal zero and the net normal momentum flux must equal the local pressure at the facet.
- the components of the combined received and transferred momentums that are perpendicular to the normal n a of the facet i.e., the tangential components
- the difference between the components of the combined received and transferred momentums that are parallel to the normal n a of the facet i.e., the normal components
- particles are gathered from the voxels and provided to the facets (step 308).
- the flux of state i particles between a voxel N(x) and a facet F a . is:
- Vm (x) has a non-zero value
- the size of the facets is selected so that Via (x) has a non-zero value for only a small number of voxels. Because V w . (x) d P/(x) may have non-integer values, T a (x) is stored and processed as a real number.
- the state vector N(a) for the facet also referred to as a facet distribution function, has 54 entries corresponding to the 54 entries of the voxel state vectors.
- the input states of the facet distribution function N(a) are set equal to the flux of particles into those states divided by the volume V w . :
- the facet distribution function is a simulation tool for generating the output flux from a facet, and is not necessarily representative of actual particles. To generate an accurate output flux, values are assigned to the other states of the distribution function. Outward states are populated using the technique described above for populating the inward states:
- TIOTHER (a) is determined using the technique described above for generating TUN (a), but applying the technique to states (a n a . ⁇ 0) other than incoming states (ci no. ⁇ 0)).
- TIOTHER (a) may be generated using values of TIOUT (a) from the previous time step so that:
- N (a) for parallel states is determined as the limit ⁇ ( ⁇ ) as V w . and V w .(x) approach zero.
- states having zero velocity i.e., rest states and states (0, 0, 0, 2) and (0, 0, 0, -2) are initialized at the beginning of the simulation based on initial conditions for temperature and pressure. These values are then adjusted over time.
- step 312 surface dynamics are performed for each facet to satisfy the four boundary conditions discussed above (step 312).
- a procedure for performing surface dynamics for a facet is illustrated in FIG. 11. Initially, the combined momentum normal to the facet F a . is determined (step 1105) by determining the combined momentum P(a) of the particles at the facet as:
- This normal momentum is then eliminated using a pushing/pulling technique (step 1110) to produce N n -(a).
- a pushing/pulling technique (step 1110) to produce N n -(a).
- particles are moved between states in a way that affects only normal momentum.
- the pushing/pulling technique is described in U.S. Pat. No. 5,594,671, which is incorporated by reference.
- a Boltzmann distribution may be achieved by applying a set of collision rules
- An outgoing flux distribution for the facet F a . is then determined (step 1120) based on the incoming flux distribution and the Boltzmann distribution. First, the difference between the incoming flux distribution ⁇ ; (a) and the Boltzmann distribution is determined as:
- TIOUT (a)Vm -. ⁇ . ⁇ (a), Eq.(23) for ri Ci >0 and where z* is the state having a direction opposite to state i. For example, if state i is (1, 1, 0, 0), then state /* is (-1, -1, 0, 0). To account for skin friction and other factors, the outgoing flux distribution may be further refined to: riOUT(a) N n-Bi( a ) V ia - ⁇ >( ⁇ ) +
- ANj and AN j,2 are distribution functions corresponding to the energy (j) of the state i and the indicated tangential vector.
- the distribution functions are determined according to:
- AN j,1 ,2 - " ⁇ 2 ( n « ? c i c i N n-BI ( ⁇ ) " ⁇ 1 ,2 ⁇ ) Eq.(25) where j equals 1 for energy level 1 states and 2 for energy level 2 states.
- the functions of each term of the equation for ⁇ (a) are as follows.
- the first and second terms enforce the normal momentum flux boundary condition to the extent that collisions have been effective in producing a Boltzmann distribution, but include a tangential momentum flux anomaly.
- the fourth and fifth terms correct for this anomaly, which may arise due to discreteness effects or non-Boltzmann structure due to insufficient collisions.
- the third term adds a specified amount of skin fraction to enforce a desired change in tangential momentum flux on the surface. Generation of the friction coefficient C/is described below. Note that all terms involving vector manipulations are geometric factors that may be calculated prior to beginning the simulation.
- the difference between the input energy and the output energy is measured for each energy level j as: where the index j denotes the energy of the state i. This energy difference is then used to generate a difference term:
- particles are moved between voxels along the three- dimensional rectilinear lattice (step 314).
- This voxel to voxel movement is the only movement operation performed on voxels that do not interact with the facets (i.e., voxels that are not located near a surface).
- voxels that are not located near enough to a surface to interact with the surface constitute a large majority of the voxels.
- Each of the separate states represents particles moving along the lattice with integer speeds in each of the three dimensions: x, y, and z.
- the integer speeds include: 0, ⁇ 1, and ⁇ 2.
- the sign of the speed indicates the direction in which a particle is moving along the corresponding axis.
- the entire population of a state is moved from its current voxel to its destination voxel during every time increment.
- the particles of the destination voxel are moved from that voxel to their own destination voxels.
- an energy level 1 particle that is moving in the +lx and +ly direction (1, 0, 0) is moved from its current voxel to one that is +1 over in the x direction and 0 for other direction.
- the particle ends up at its destination voxel with the same state it had before the move (1,0,0). Interactions within the voxel will likely change the particle count for that state based on local interactions with other particles and surfaces.
- the particle will continue to move along the lattice at the same speed and direction.
- the move operation becomes slightly more complicated for voxels that interact with one or more surfaces. This can result in one or more fractional particles being transferred to a facet. Transfer of such fractional particles to a facet results in fractional particles remaining in the voxels. These fractional particles are transferred to a voxel occupied by the facet. For example, referring to FIG. 9, when a portion 900 of the state i particles for a voxel 905 is moved to a facet 910 (step 308), the remaining portion 915 is moved to a voxel 920 in which the facet 910 is located and from which particles of state i are directed to the facet 910.
- N(x) is the source voxel.
- step 316 the outgoing particles from each facet are scattered to the voxels.
- this step is the reverse of the gather step by which particles were moved from the voxels to the facets.
- the number of state i particles that move from a facet F a to a voxel ⁇ ( ⁇ ) is:
- N ctlF-V V ai ( ⁇ ) r alOUT f /V al Eq.(35)
- Vi(x) accounts for the volume reduction of partial voxels. From this, for each state i, the total number of particles directed from the facets to a voxel N(3 ⁇ 4 is:
- an amount of mass equal to the value gained (due to underflow) or lost (due to overflow) is added back to randomly (or sequentially) selected states having the same energy and that are not themselves subject to overflow or underflow.
- the additional momentum resulting from this addition of mass and energy is accumulated and added to the momentum from the truncation.
- both mass and energy are corrected when the mass counter reaches zero.
- the momentum is corrected using pushing/pulling techniques until the momentum accumulator is returned to zero.
- fluid dynamics are performed (step 318).
- This step may be referred to as microdynamics or intravoxel operations.
- the advection procedure may be referred to as intervoxel operations.
- the microdynamics operations described below may also be used to collide particles at a facet to produce a Boltzmann distribution.
- Equation 1 The fluid dynamics is ensured in the lattice Boltzmann equation models by a particular collision operator known as the BGK collision model.
- This collision model mimics the dynamics of the distribution in a real fluid system.
- the collision process can be well described by the right-hand side of Equation 1 and Equation 2.
- Equation 3 the conserved quantities of a fluid system, specifically the density, momentum and the energy are obtained from the distribution function using Equation 3.
- the equilibrium distribution function noted by f eq in equation (2), is fully specified by Equation (4).
- the choice of the velocity vector set Ci, the weights, both are listed in Table 1, together with Equation 2 ensures that the macroscopic behavior obeys the correct hydrodynamic equation.
- variable resolution employs voxels of different sizes, hereinafter referred to as coarse voxels 12000 and fine voxels 1205.
- coarse voxels 12000 and fine voxels 1205.
- fine voxels 1205. The interface between regions of coarse and fine voxels is referred to as a variable resolution (VR) interface 1210.
- VR variable resolution
- facets may interact with voxels on both sides of the VR interface. These facets are classified as VR interface facets 1215 (Faic) or VR fine facets 1220 (FOIF).
- a VR interface facet 1215 is a facet positioned on the coarse side of the VR interface and having a coarse parallelepiped 1225 extending into a fine voxel.
- a coarse parallelepiped is one for which ci is dimensioned according to the dimensions of a coarse voxel, while a fine parallelepiped is one for which Ci is dimensioned according to the dimensions of a fine voxel.
- a VR fine facet 1220 is a facet positioned on the fine side of the VR interface and having a fine parallelepiped 1230 extending into a coarse voxel. Processing related to interface facets may also involve interactions with coarse facets 1235 (F a c) and fine facets 1240 (FOF).
- VR facets For both types of VR facets, surface dynamics are performed at the fine scale, and operate as described above. However, VR facets differ from other facets with respect to the way in which particles advect to and from the VR facets.
- Interactions with VR facets are handled using a variable resolution procedure 1300 illustrated in FIG. 13. Most steps of this procedure are carried out using the comparable steps discussed above for interactions with non-VR facets.
- the procedure 1300 is performed during a coarse time step (i.e., a time period corresponding to a coarse voxel) that includes two phases that each correspond to a fine time step.
- the facet surface dynamics are performed during each fine time step.
- a VR interface facet Faic is considered as two identically sized and oriented fine facets that are referred to, respectively, as a black facet Faicb and a red facet Faicr.
- the black facet Faicb is associated with the first fine time step within a coarse time step while the red facet Faio is associated with the second fine time step within a coarse time step.
- particles are moved (advected) between facets by a first surface-to- surface advection stage (step 1302).
- Particles are moved from black facets Faicb to coarse facets Ffic with a weighting factor of V- ⁇ that corresponds to the volume of the unblocked portion of the coarse parallelepiped (FIG. 12, 1225) that extends from a facet F a . and that lies behind a facet Fp less the unblocked portion of the fine parallelepiped (FIG. 12, 1245) that extends from the facet F a . and that lies behind the facet Fp.
- the magnitude of a for a fine voxel is one half the magnitude of a for a coarse voxel.
- the volume of a parallelepiped for a facet Fa is defined as:
- the volume of a fine parallelepiped corresponding to a facet is one half the volume of the corresponding coarse parallelepiped for the facet.
- Particles are moved from coarse facets F a .c to black facets Fpicb with a weighting factor of Vaf) that corresponds to the volume of the unblocked portion of the fine parallelepiped that extends from a facet F a . and that lies behind a facet Fp.
- Particles are moved from red facets Faicr to coarse facets Fpc with a weighting factor of Vaf), and from coarse facets F a .c to red facets Fpicr with a weighting factor of V- ⁇ .
- Particles are moved from red facets Faicr to black facets Fpicb with a weighting factor of Vaf
- black-to-red advections do not occur.
- black and red facets represent consecutive time steps, black-to-black advections (or red- to-red advections) never occur.
- particles in this stage are moved from red facets Faicr to fine facets FpiF or Ffw with a weighting factor of Vaf), and from fine facets FaiF or F 0 .F to black facets Faicb with the same weighting factor.
- particles are moved from fine facets F a .iF or F 0 F to other fine facets FpiF or Ff)F with the same weighting factor, and from coarse facets F a .c to other coarse facets Fc with a weighting factor of Vcafi that corresponds to the volume of the unblocked portion of the coarse parallelepiped that extends from a facet Fa and that lies behind a facet Ff
- particles are gathered from the voxels in a first gather stage (steps 1304-1310).
- Particles are gathered for fine facets F a p from fine voxels using fine parallelepipeds (step 1304), and for coarse facets F a .c from coarse voxels using coarse parallelepipeds (step 1306). Particles are then gathered for black facets FaiRb and for VR fine facets F 0 .IF from both coarse and fine voxels using fine parallelepipeds (step 1308). Finally, particles are gathered for red facets Fain- from coarse voxels using the differences between coarse parallelepipeds and fine paralllelepipeds (step 1310).
- coarse voxels that interact with fine voxels or VR facets are exploded into a collection of fine voxels (step 1312).
- the states of a coarse voxel that will transmit particles to a fine voxel within a single coarse time step are exploded.
- the appropriate states of a coarse voxel that is not intersected by a facet are exploded into eight fine voxels oriented like the microblock of FIG. 4.
- the appropriate states of coarse voxel that is intersected by one or more facets are exploded into a collection of complete and/or partial fine voxels corresponding to the portion of the coarse voxel that is not intersected by any facets.
- the particle densities N (x) for a coarse voxel and the fine voxels resulting from the explosion thereof are equal, but the fine voxels may have fractional factors Pf that differ from the fractional factor of the coarse voxel and from the fractional factors of the other fine voxels.
- particles are moved between fine voxels (step 1318) including actual fine voxels and fine voxels resulting from the explosion of coarse voxels. Once the particles have been moved, particles are scattered from the fine facets F 0 .IF and F a p to the fine voxels (step 1320).
- Particles are also scattered from the black facets Faicb to the fine voxels (including the fine voxels that result from exploding a coarse voxel) (step 1322). Particles are scattered to a fine voxel if the voxel would have received particles at that time absent the presence of a surface.
- particles are scattered to a voxel N(x) when the voxel is an actual fine voxel (as opposed to a fine voxel resulting from the explosion of a coarse voxel), when a voxel N(x+a) that is one velocity unit beyond the voxel N(x) is an actual fine voxel, or when the voxel N(x+a) that is one velocity unit beyond the voxel N(x) is a fine voxel resulting from the explosion of a coarse voxel.
- the first fine time step is completed by performing fluid dynamics on the fine voxels (step 1324).
- the voxels for which fluid dynamics are performed do not include the fine voxels that result from exploding a coarse voxel (step 1312).
- the procedure 1300 implements similar steps during the second fine time step. Initially, particles are moved between surfaces in a second surface-to-surface advection stage (step 1326). Particles are advected from black facets to red facets, from black facets to fine facets, from fine facets to red facets, and from fine facets to fine facets.
- particles are gathered from the voxels in a second gather stage (steps 1328-1330). Particles are gathered for red facets FaiRr from fine voxels using fine parallelepipeds (step 1328). Particles also are gathered for fine facets F a p and F 0 .IF from fine voxels using fine parallelepipeds (step 1330).
- step 1332 surface dynamics are performed for the fine facets F 0 .IF and F a p (step 1332), for the coarse facets F a .c (step 1 134), and for the red facets Faicr (step 1336) as discussed above.
- particles are moved between voxels using fine resolution (step 1338) so that particles are moved to and from fine voxels and fine voxels representative of coarse voxels.
- Particles are then moved between voxels using coarse resolution (step 1340) so that particles are moved to and from coarse voxels.
- particles are scattered from the facets to the voxels while the fine voxels that represent coarse voxels (i.e., the fine voxels resulting from exploding coarse voxels) are coalesced into coarse voxels (step 1342).
- particles are scattered from coarse facets to coarse voxels using coarse voxels.
- FIG. 14 illustrates an example of a perforated sheet 1400.
- the perforations 1402 themselves can also be of different shapes and staggering on the surface so that the perforated partem achieves a wide range of open to closed surface area ratios also reaching very small perforations.
- the sheets 1400 can be rigid or flexible so that they can be foldable like a textile fabric. In addition these sheets or panels are sometimes combined in a multilayer fashion with other acoustic damping materials (such as foams) to increase their noise reduction effect (not shown).
- perforated sheets can be installed on the surfaces that generate or reflect acoustic waves, hence corresponding to noise sources, in order to absorb these and overall reduce the noise perception for the surrounding environment.
- Large scale such as in rooms or on buildings as well as small scale installations such as around components of machinery can be found.
- these installations are effective in reducing noise from several components such as high-lift devices and landing gears. They can be used e.g. as solid or flexible fairings (elastic membranes) around the landing gear components and doors.
- the first set of measureable qualities can include geometric characteristics of the materials from which the panels are made, including, for example, the thickness of the panel, the porosity (e.g., ratio between open to closed area (or volume)), and the surface roughness.
- the second set of measurable qualities can include physical characteristics of the panel, including, for example, resistivity for a range of velocities, (e.g., the hydrodynamic pressure drop for a given velocity) and acoustic impedance (e.g., he acoustic pressure damping resulting in an acoustic absorption of as a function of frequency). In general, the physical characteristics may be described for the normal direction perpendicular to the panel surface.
- a mesh 1508 affecting the fluid flow across a fluid flow region 1502, 1506 may be modeled as a two dimensional interface 1508 crossing the fluid flow region 1502, 1506.
- a two dimensional interface is an interface that may have length and width (and shape) but no depth / thickness (or an insignificant depth / thickness).
- the two-dimensional interface may form a plane, a curve, a cylinder, or any other shape.
- Modeling the mesh as a two-dimensional interface enables a more efficient computer simulation of the fluid flow region.
- the complexity inherent in modeling the mesh is reduced to a barrier that enables fluid across the boundary based on the measure ⁇ .
- the computer processor performs the simulation more efficiently reducing the processor and memory requirements to perform the simulation.
- a system may account for example for a surface porosity ⁇ 1504, which represents a situation where a thin sheet with small holes crosses the fluid flow region. The flow is partially blocked from both sides.
- a surface porosity ⁇ 1504 represents a situation where a thin sheet with small holes crosses the fluid flow region. The flow is partially blocked from both sides.
- This surface porosity introduces a degree of freedom for modeling of interface properties.
- One (and not the only one) of the immediate applications is noise reduction of airplane wings partially covered by thin sheet with small holes for acoustic damping. Additional parameters can be introduced in the model to add degrees of freedom for modeling of the interface properties (such as interface thickness, hole diameters, etc).
- the interface 1508 (e.g. a mesh sheet) can be described by so-called double-sided surface elements (i.e., surfels.
- double-sided surfels a set of paired surfels S form a double-layered surface having an inner surface A and outer surface B.
- the inner surface A interacts with the first side 1502 and the outer surface B interacts with second side 1506.
- each inner surfel has the exact same shape and size as its paired outer surfel, and each inner surfel is only in touch with the paired outer surfel.
- the standard surfel gather and scatter scheme is performed on each side of the surface A, B, and with the condition that the ⁇ fraction of incoming particles from the first side 1502 pass through to the second side side 1506 while all of the incoming particles ⁇ from the second side 1506 pass through to the first side 1502.
- Advantages of this approach include simplified handling of the complex interface, exact satisfaction of conservation laws, and easy realization of specified fluid boundary conditions on interface.
- the pressure on the first side 1502 of the interface 1508 can be determined to be different than the pressure on the second side 1506 of the interface 1508. As air passes from the first side 1502 of the interface to the second side 1508 of the interface 1508, the pressure on the second side 1508 increases. During a simulation, this effect can be calculated using the fluid flow from voxels on one side of the interface to voxels on the second side of the interface. The flow of across the interface can be used to calculate both acoustic effects and changes in the fluid flow. Modeling different perforated sheets can be performed by modifying the inputs into the model to calculate ⁇ .
- the operations described in this specification can be implemented as operations performed by a data processing apparatus on data stored on one or more computer- readable storage devices or received from other sources.
- the term "data processing apparatus” encompasses all kinds of apparatus, devices, and machines for processing data, including by way of example: a programmable processor, a computer, a system on a chip, or multiple ones, or combinations, of the foregoing.
- the apparatus can include special purpose logic circuitry (e.g., an FPGA (field programmable gate array) or an ASIC (application specific integrated circuit)).
- the apparatus can also include, in addition to hardware, code that creates an execution environment for the computer program in question (e.g., code that constitutes processor firmware, a protocol stack, a database management system, an operating system, a cross- platform runtime environment, a virtual machine, or a combination of one or more of them).
- the apparatus and execution environment can realize various different computing model infrastructures, such as web services, distributed computing and grid computing infrastructures.
- a computer program (also known as a program, software, software application, script, or code) can be written in any form of programming language, including compiled or interpreted languages, declarative or procedural languages, and it can be deployed in any form, including as a stand-alone program or as a module, component, subroutine, object, or other unit suitable for use in a computing environment.
- a computer program may, but need not, correspond to a file in a file system.
- a program can be stored in a portion of a file that holds other programs or data (e.g., one or more scripts stored in a markup language document), in a single file dedicated to the program in question, or in multiple coordinated files (e.g., files that store one or more modules, sub programs, or portions of code).
- a computer program can be deployed to be executed on one computer or on multiple computers that are located at one site or distributed across multiple sites and interconnected by a communication network.
- the processes and logic flows described in this specification can be performed by one or more programmable processors executing one or more computer programs to perform actions by operating on input data and generating output.
- the processes and logic flows can also be performed by, and apparatus can also be implemented as, special purpose logic circuitry (e.g., an FPGA (field programmable gate array) or an ASIC (application specific integrated circuit)).
- special purpose logic circuitry e.g., an FPGA (field programmable gate array) or an ASIC (application specific integrated circuit)
- processors suitable for the execution of a computer program include, by way of example, both general and special purpose microprocessors, and any one or more processors of any kind of digital computer.
- a processor will receive instructions and data from a read only memory or a random access memory or both.
- the essential elements of a computer are a processor for performing actions in accordance with instructions and one or more memory devices for storing instructions and data.
- a computer will also include, or be operatively coupled to receive data from or transfer data to, or both, one or more mass storage devices for storing data (e.g., magnetic, magneto optical disks, or optical disks), however, a computer need not have such devices.
- a computer can be embedded in another device (e.g., a mobile telephone, a personal digital assistant (PDA), a mobile audio or video player, a game console, a Global Positioning System (GPS) receiver, or a portable storage device (e.g., a universal serial bus (USB) flash drive)).
- Devices suitable for storing computer program instructions and data include all forms of non-volatile memory, media and memory devices, including by way of example, semiconductor memory devices (e.g., EPROM, EEPROM, and flash memory devices), magnetic disks (e.g., internal hard disks or removable disks), magneto optical disks, and CD ROM and DVD-ROM disks.
- the processor and the memory can be supplemented by, or incorporated in, special purpose logic circuitry.
- embodiments of the subject matter described in this specification can be implemented on a computer having a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user and a keyboard and a pointing device (e.g., a mouse or a trackball) by which the user can provide input to the computer.
- a display device e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor
- keyboard and a pointing device e.g., a mouse or a trackball
- Other kinds of devices can be used to provide for interaction with a user as well; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback) and input from the user can be received in any form, including acoustic, speech, or tactile input.
- feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or
- a computer can interact with a user by sending documents to and receiving documents from a device that is used by the user (for example, by sending web pages to a web browser on a user's user device in response to requests received from the web browser).
- a computing system that includes a back end component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front end component (e.g., a user computer having a graphical user interface or a Web browser through which a user can interact with an implementation of the subject matter described in this specification), or any combination of one or more such back end, middleware, or front end components.
- the components of the system can be
- Examples of communication networks include a local area network (“LAN”) and a wide area network (“WAN”), an inter-network (e.g., the
- peer-to-peer networks e.g., ad hoc peer-to-peer networks.
- the computing system can include users and servers.
- a user and server are generally remote from each other and typically interact through a communication network. The relationship of user and server arises by virtue of computer programs running on the respective computers and having a user-server relationship to each other.
- a server transmits data (e.g., an HTML page) to a user device (e.g., for purposes of displaying data to and receiving user input from a user interacting with the user device).
- Data generated at the user device e.g., a result of the user interaction
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Geometry (AREA)
- General Physics & Mathematics (AREA)
- Evolutionary Computation (AREA)
- General Engineering & Computer Science (AREA)
- Computer Hardware Design (AREA)
- Automation & Control Theory (AREA)
- Aviation & Aerospace Engineering (AREA)
- Computational Mathematics (AREA)
- Mathematical Analysis (AREA)
- Mathematical Optimization (AREA)
- Pure & Applied Mathematics (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
Description
Claims
Applications Claiming Priority (2)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
US15/729,216 US11042674B2 (en) | 2017-10-10 | 2017-10-10 | Acoustic effects of a mesh on a fluid flow |
PCT/US2018/055220 WO2019075068A1 (en) | 2017-10-10 | 2018-10-10 | Acoustic effects of a mesh on a fluid flow |
Publications (3)
Publication Number | Publication Date |
---|---|
EP3695333A1 true EP3695333A1 (en) | 2020-08-19 |
EP3695333A4 EP3695333A4 (en) | 2020-12-02 |
EP3695333B1 EP3695333B1 (en) | 2023-07-19 |
Family
ID=65994048
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
EP18866750.5A Active EP3695333B1 (en) | 2017-10-10 | 2018-10-10 | Acoustic effects of a mesh on a fluid flow |
Country Status (4)
Country | Link |
---|---|
US (1) | US11042674B2 (en) |
EP (1) | EP3695333B1 (en) |
JP (1) | JP7025538B2 (en) |
WO (1) | WO2019075068A1 (en) |
Families Citing this family (10)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN110188462A (en) * | 2019-05-29 | 2019-08-30 | 无锡恒鼎超级计算中心有限公司 | LBM algorithm optimization method based on martial prowess framework |
CN110795845B (en) * | 2019-10-28 | 2021-09-03 | 浙江大学 | Heat supply system margin quantitative calculation method and system |
CN110750847B (en) * | 2019-10-29 | 2021-06-15 | 中国科学院过程工程研究所 | Method, device, equipment and medium for determining grid segmentation relation |
CN111353253B (en) * | 2020-03-31 | 2020-12-01 | 温州科技职业学院 | Method for realizing multi-column waves with different parameters based on Flow-3D software simulated physical wave-making means |
CN112380786B (en) * | 2020-10-30 | 2024-04-05 | 中国运载火箭技术研究院 | Air rudder thermal environment modeling method, equipment and storage medium |
CN112464589B (en) * | 2020-12-11 | 2023-02-03 | 国网新疆电力有限公司电力科学研究院 | Simplified numerical simulation method for aerodynamic resistance of power transmission conductor |
CN114492225B (en) * | 2021-12-28 | 2024-07-12 | 中国航天空气动力技术研究院 | Streamline visualization method based on cluster screening |
CN114462257B (en) * | 2022-04-11 | 2023-01-31 | 中国空气动力研究与发展中心计算空气动力研究所 | Flow oscillation control method for landing gear bay of aviation aircraft |
CN114580221B (en) * | 2022-05-07 | 2022-07-22 | 中国空气动力研究与发展中心计算空气动力研究所 | Method for rapidly calculating cross-basin gap flow |
CN115034062A (en) * | 2022-06-13 | 2022-09-09 | 南京航空航天大学 | Off-site route noise evaluation method considering plateau airport meteorological conditions |
Family Cites Families (10)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US5377129A (en) | 1990-07-12 | 1994-12-27 | Massachusetts Institute Of Technology | Particle interaction processing system |
US6221258B1 (en) | 1996-06-14 | 2001-04-24 | Case Western Reserve University | Method and apparatus for acoustically driven media filtration |
US20040059265A1 (en) | 2002-09-12 | 2004-03-25 | The Regents Of The University Of California | Dynamic acoustic focusing utilizing time reversal |
US6933719B2 (en) | 2003-07-03 | 2005-08-23 | Exxonmobil Research And Engineering Co. | Fluid flow properties from acoustically stimulated NMR |
GB2466899B (en) * | 2007-11-30 | 2012-01-11 | Shell Int Research | Real time completion monitoring with acoustic waves |
KR101192335B1 (en) * | 2011-05-16 | 2012-10-26 | 한국과학기술연구원 | Method for simulating fluid flow and recording medium for performing the method |
US9037440B2 (en) * | 2011-11-09 | 2015-05-19 | Exa Corporation | Computer simulation of fluid flow and acoustic behavior |
CA2912674C (en) * | 2013-05-16 | 2021-05-18 | Exa Corporation | Mass exchange model for relative permeability simulation |
US10232549B2 (en) | 2015-09-10 | 2019-03-19 | The Boeing Company | Geometric sound absorption via additive manufacturing |
US20180168457A1 (en) * | 2016-12-19 | 2018-06-21 | Canon Kabushiki Kaisha | Holding member and holding member set, masking member and masking member set, and photoacoustic apparatus |
-
2017
- 2017-10-10 US US15/729,216 patent/US11042674B2/en active Active
-
2018
- 2018-10-10 JP JP2020520470A patent/JP7025538B2/en active Active
- 2018-10-10 EP EP18866750.5A patent/EP3695333B1/en active Active
- 2018-10-10 WO PCT/US2018/055220 patent/WO2019075068A1/en unknown
Also Published As
Publication number | Publication date |
---|---|
US11042674B2 (en) | 2021-06-22 |
EP3695333B1 (en) | 2023-07-19 |
US20190108296A1 (en) | 2019-04-11 |
JP2021513692A (en) | 2021-05-27 |
EP3695333A4 (en) | 2020-12-02 |
CN113168493A (en) | 2021-07-23 |
WO2019075068A1 (en) | 2019-04-18 |
JP7025538B2 (en) | 2022-02-24 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
EP3695333B1 (en) | Acoustic effects of a mesh on a fluid flow | |
JP6589001B2 (en) | Computer simulation of fluid flow and acoustic behavior | |
US10831952B2 (en) | Data processing method for including the effect of the tortuosity on the acoustic behavior of a fluid in a porous medium | |
US9542506B2 (en) | Computer simulation of physical processes including modeling of laminar-to-turbulent transition | |
AU2012348365A1 (en) | Computer simulation of physical processes | |
AU2014296132A1 (en) | Temperature coupling algorithm for hybrid Thermal Lattice Boltzmann method | |
EP3525120A1 (en) | Lattice boltzmann collision operators enforcing isotropy and galilean invariance | |
EP3816842A1 (en) | Computer system for simulating physical process using lattice boltzmann based scalar transport enforcing galilean invariance for scalar transport | |
US11188692B2 (en) | Turbulent boundary layer modeling via incorporation of pressure gradient directional effect | |
EP3809306A1 (en) | Method and apparatus for automatic underhood thermal modeling | |
US20200285709A1 (en) | Turbulent Boundary Layer Modeling via Incorporation of Pressure Gradient Directional Effect | |
Li et al. | Compressive properties of Min-mod-type limiters in modelling shockwave-containing flows | |
Kholodar et al. | Deformation of unstructured viscous grids | |
CN113168493B (en) | System for determining fluid flow and acoustic wave propagation through three-dimensional porous material | |
Atak et al. | Discontinuous Galerkin for high performance computational fluid dynamics | |
EP3809307A1 (en) | Method for automatic detection of axial cooling fan rotation direction | |
Kosík | The CFD simulation of the flow around the aircraft using OpenFOAM and ANSA | |
Melson et al. | Multigrid Acceleration of Time-Accurate Navier-Stokes Calculations | |
Kozubskaya et al. | Quasi-1D edge-based schemes on unstructured meshes for solving aerodynamics and aeroacoustics problems | |
Kam | A three-dimensional Newton-Krylov Navier-Stokes flow solver using a one-equation turbulence model | |
Ferrari et al. | Modelling and fast numerical methods for granular flows | |
Tubbs | Lattice Boltzmann simulation of flow around bluff-bodies |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
STAA | Information on the status of an ep patent application or granted ep patent |
Free format text: STATUS: THE INTERNATIONAL PUBLICATION HAS BEEN MADE |
|
PUAI | Public reference made under article 153(3) epc to a published international application that has entered the european phase |
Free format text: ORIGINAL CODE: 0009012 |
|
STAA | Information on the status of an ep patent application or granted ep patent |
Free format text: STATUS: REQUEST FOR EXAMINATION WAS MADE |
|
17P | Request for examination filed |
Effective date: 20200508 |
|
AK | Designated contracting states |
Kind code of ref document: A1 Designated state(s): AL AT BE BG CH CY CZ DE DK EE ES FI FR GB GR HR HU IE IS IT LI LT LU LV MC MK MT NL NO PL PT RO RS SE SI SK SM TR |
|
AX | Request for extension of the european patent |
Extension state: BA ME |
|
RAP1 | Party data changed (applicant data changed or rights of an application transferred) |
Owner name: DASSAULT SYSTEMES SIMULIA CORP. |
|
A4 | Supplementary search report drawn up and despatched |
Effective date: 20201030 |
|
RIC1 | Information provided on ipc code assigned before grant |
Ipc: G06F 30/23 20200101ALI20201026BHEP Ipc: G06F 30/15 20200101AFI20201026BHEP Ipc: G06F 119/10 20200101ALI20201026BHEP |
|
DAV | Request for validation of the european patent (deleted) | ||
DAX | Request for extension of the european patent (deleted) | ||
REG | Reference to a national code |
Ref country code: DE Ref legal event code: R079 Ref document number: 602018053801 Country of ref document: DE Free format text: PREVIOUS MAIN CLASS: G06F0017500000 Ipc: G06F0030150000 Ref country code: DE Ref legal event code: R079 Free format text: PREVIOUS MAIN CLASS: G06F0017500000 Ipc: G06F0030150000 |
|
STAA | Information on the status of an ep patent application or granted ep patent |
Free format text: STATUS: EXAMINATION IS IN PROGRESS |
|
RIC1 | Information provided on ipc code assigned before grant |
Ipc: G06F 119/10 20200101ALI20220310BHEP Ipc: G06F 30/23 20200101ALI20220310BHEP Ipc: G06F 30/15 20200101AFI20220310BHEP |
|
17Q | First examination report despatched |
Effective date: 20220401 |
|
GRAP | Despatch of communication of intention to grant a patent |
Free format text: ORIGINAL CODE: EPIDOSNIGR1 |
|
STAA | Information on the status of an ep patent application or granted ep patent |
Free format text: STATUS: GRANT OF PATENT IS INTENDED |
|
INTG | Intention to grant announced |
Effective date: 20230213 |
|
GRAS | Grant fee paid |
Free format text: ORIGINAL CODE: EPIDOSNIGR3 |
|
GRAA | (expected) grant |
Free format text: ORIGINAL CODE: 0009210 |
|
STAA | Information on the status of an ep patent application or granted ep patent |
Free format text: STATUS: THE PATENT HAS BEEN GRANTED |
|
AK | Designated contracting states |
Kind code of ref document: B1 Designated state(s): AL AT BE BG CH CY CZ DE DK EE ES FI FR GB GR HR HU IE IS IT LI LT LU LV MC MK MT NL NO PL PT RO RS SE SI SK SM TR |
|
REG | Reference to a national code |
Ref country code: GB Ref legal event code: FG4D |
|
REG | Reference to a national code |
Ref country code: CH Ref legal event code: EP |
|
REG | Reference to a national code |
Ref country code: DE Ref legal event code: R096 Ref document number: 602018053801 Country of ref document: DE |
|
P01 | Opt-out of the competence of the unified patent court (upc) registered |
Effective date: 20230630 |
|
REG | Reference to a national code |
Ref country code: IE Ref legal event code: FG4D |
|
REG | Reference to a national code |
Ref country code: LT Ref legal event code: MG9D |
|
REG | Reference to a national code |
Ref country code: NL Ref legal event code: MP Effective date: 20230719 |
|
REG | Reference to a national code |
Ref country code: AT Ref legal event code: MK05 Ref document number: 1590201 Country of ref document: AT Kind code of ref document: T Effective date: 20230719 |
|
PG25 | Lapsed in a contracting state [announced via postgrant information from national office to epo] |
Ref country code: NL Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT Effective date: 20230719 |
|
PG25 | Lapsed in a contracting state [announced via postgrant information from national office to epo] |
Ref country code: GR Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT Effective date: 20231020 |
|
PGFP | Annual fee paid to national office [announced via postgrant information from national office to epo] |
Ref country code: GB Payment date: 20231027 Year of fee payment: 6 |
|
PG25 | Lapsed in a contracting state [announced via postgrant information from national office to epo] |
Ref country code: IS Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT Effective date: 20231119 |
|
PG25 | Lapsed in a contracting state [announced via postgrant information from national office to epo] |
Ref country code: SE Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT Effective date: 20230719 Ref country code: RS Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT Effective date: 20230719 Ref country code: PT Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT Effective date: 20231120 Ref country code: NO Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT Effective date: 20231019 Ref country code: LV Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT Effective date: 20230719 Ref country code: LT Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT Effective date: 20230719 Ref country code: IS Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT Effective date: 20231119 Ref country code: HR Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT Effective date: 20230719 Ref country code: GR Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT Effective date: 20231020 Ref country code: FI Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT Effective date: 20230719 Ref country code: AT Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT Effective date: 20230719 |
|
PGFP | Annual fee paid to national office [announced via postgrant information from national office to epo] |
Ref country code: FR Payment date: 20231025 Year of fee payment: 6 Ref country code: DE Payment date: 20231027 Year of fee payment: 6 |
|
PG25 | Lapsed in a contracting state [announced via postgrant information from national office to epo] |
Ref country code: PL Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT Effective date: 20230719 |
|
REG | Reference to a national code |
Ref country code: DE Ref legal event code: R097 Ref document number: 602018053801 Country of ref document: DE |
|
PG25 | Lapsed in a contracting state [announced via postgrant information from national office to epo] |
Ref country code: ES Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT Effective date: 20230719 |
|
PG25 | Lapsed in a contracting state [announced via postgrant information from national office to epo] |
Ref country code: SM Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT Effective date: 20230719 Ref country code: RO Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT Effective date: 20230719 Ref country code: ES Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT Effective date: 20230719 Ref country code: EE Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT Effective date: 20230719 Ref country code: DK Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT Effective date: 20230719 Ref country code: CZ Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT Effective date: 20230719 Ref country code: SK Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT Effective date: 20230719 |
|
PLAA | Information modified related to event that no opposition was filed |
Free format text: ORIGINAL CODE: 0009299DELT |
|
PLBE | No opposition filed within time limit |
Free format text: ORIGINAL CODE: 0009261 |
|
STAA | Information on the status of an ep patent application or granted ep patent |
Free format text: STATUS: NO OPPOSITION FILED WITHIN TIME LIMIT |
|
PG25 | Lapsed in a contracting state [announced via postgrant information from national office to epo] |
Ref country code: MC Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT Effective date: 20230719 Ref country code: IT Free format text: LAPSE BECAUSE OF FAILURE TO SUBMIT A TRANSLATION OF THE DESCRIPTION OR TO PAY THE FEE WITHIN THE PRESCRIBED TIME-LIMIT Effective date: 20230719 |
|
REG | Reference to a national code |
Ref country code: CH Ref legal event code: PL |
|
REG | Reference to a national code |
Ref country code: BE Ref legal event code: MM Effective date: 20231031 |
|
PG25 | Lapsed in a contracting state [announced via postgrant information from national office to epo] |
Ref country code: LU Free format text: LAPSE BECAUSE OF NON-PAYMENT OF DUE FEES Effective date: 20231010 |
|
R26N | No opposition filed (corrected) |
Effective date: 20240422 |
|
PG25 | Lapsed in a contracting state [announced via postgrant information from national office to epo] |
Ref country code: LU Free format text: LAPSE BECAUSE OF NON-PAYMENT OF DUE FEES Effective date: 20231010 |
|
REG | Reference to a national code |
Ref country code: GB Ref legal event code: 732E Free format text: REGISTERED BETWEEN 20240620 AND 20240627 |
|
PG25 | Lapsed in a contracting state [announced via postgrant information from national office to epo] |
Ref country code: CH Free format text: LAPSE BECAUSE OF NON-PAYMENT OF DUE FEES Effective date: 20231031 |